Author(s)

Jing Wang¹, Qiushi Gu^2*

¹Artificial Intelligence and Language Cognition Laboratory, Beijing International Studies University, Beijing, China.
²Research Office, Beijing International Studies University, Beijing, China.

In an era of increasing globalization and multilingual interactions, translation quality assessment has become crucial. Yet, a notable gap persists in contemporary research, especially regarding standardization and systematic exploration to the quantitative assessment of translation quality, an area that has not garnered significant scholarly focus. This research provides a thorough examination of the methods and standards utilized for assessing translation quality across educational, certification, and industrial domains. Emphasizing the pivotal role of translation quality assessment in ensuring the accuracy, fluency, coherence, and appropriateness of translated materials, this paper sheds light on the existing disparities in scoring methodologies prevalent within educational and certification settings. Furthermore, it also delves into the assessment frameworks employed in industry, revealing their complexity and the detailed evaluation criteria for both human and machine-translated texts. To improve teaching efficiency and translation quality, the study proposes integrating academic and industry assessment criteria. Moreover, it envisions the evolution of future translation quality assessment models, envisaging the incorporation of advanced functionalities such as automated error detection and instantaneous feedback mechanisms aimed at optimizing the translation output.

Translation Quality, Quantitative Assessment, Educational Testing, Certification Exam, Industry Standards

Wang, J. and Gu, Q. (2024) Quantitative Assessment of Translation Quality in Education, Certification, and Industry: An Overview. Open Journal of Modern Linguistics, 14, 209-223. doi: 10.4236/ojml.2024.142012.